Enhancing capacity of a direct communication link

ABSTRACT

Capacity enhancement of a direct communication link using a variable redundancy delivery network. An estimated information rate between a source node and a terminal node may be partitioned into a first information rate provided via the direct communication link and a second information rate to be provided via the variable redundancy delivery network. One or more parameters of the variable redundancy delivery network may be calculated to provide the second information rate based on a non-uniform probability density of messages requested by the terminal node. Capacity and reliability of storage media devices in the variable redundancy delivery network may be traded off to provide the second information rate. The variable redundancy delivery network may implement various coding schemes and per-message coding rates that may be determined based on the non-uniform probability distribution of the source message library.

CROSS REFERENCES

This application is a divisional of U.S. Non-Provisional patentapplication Ser. No. 14/946,207, filed Nov. 19, 2015, and entitled,“Enhancing Capacity of a Direct Communication Link,” the contents ofwhich are incorporated by reference for all purposes.

BACKGROUND Field of the Disclosure

The present disclosure relates to broadband communications in general,and in particular, to enhancing capacity of a direct communication linkin broadband communications networks.

Relevant Background

As the use of communications and networking continues to grow around theworld, users are demanding a high-quality broadband experience even inremote areas or mobile environments. The ability to provide ahigh-quality broadband experience in these environments presents manychallenges.

SUMMARY

Methods, systems, and devices are described for capacity enhancement ofa direct communication link using a variable redundancy deliverynetwork. An estimated information rate between a source node and aterminal node may be partitioned into a first information rate providedvia the direct communication link and a second information rate to beprovided via the variable redundancy delivery network. One or moreparameters of the variable redundancy delivery network may be selectedto provide the second information rate based on a non-uniformprobability density of messages requested by the terminal node.

The variable redundancy delivery network may include multipleintermediate storage nodes in a non-redundant disk array configuration.For example, each intermediate storage node may be a logical storageunit including a storage media device. Capacity and reliability of thestorage media devices may be traded off to provide the secondinformation rate. For example, the storage media devices may be arelatively low reliability storage device (e.g., rotating disk storagemedia) having a relatively higher storage capacity. Additionally oralternatively, some intermediate storage nodes may include solid statestorage media, which typically has higher reliability but lower storagecapacity per device.

The variable redundancy delivery network may implement various codingschemes and per-message coding rates that may be determined based on anon-uniform probability distribution of messages requested by multipleusers at the terminal node. In some embodiments, the storage policy maybe an optimal policy or a heuristically determined policy.

Described aspects include a method for capacity enhancement of acommunications system including a terminal node coupled to a source nodevia a direct communications link and via a variable redundancy deliverynetwork comprising one or more intermediate storage nodes. The methodmay include determining an estimated information rate from the sourcenode to the terminal node, partitioning the estimated information rateinto a first information rate for the direct communications link and asecond information rate for the variable redundancy delivery network,wherein the first information rate is based on channel capacity of thedirect communications link, and selecting one or more parameters of thevariable redundancy delivery network to provide the second informationrate based at least in part on a non-uniform probability density of themessages, wherein the one or more parameters includes at least one of areliability characteristic of the one or more intermediate storagenodes, a storage size of the one or more intermediate storage nodes, anumber of the one or more intermediate storage nodes, or a storagepolicy for storage of messages distributed to the terminal node in theone or more intermediate storage nodes, and wherein the storage policycomprises variable redundancy for the storage of the messages accordingto a redundancy coding scheme.

Other described aspects include a method for capacity enhancement of acommunications system is described, the method comprising repeatedlydelivering a plurality of messages of a finite message library to aterminal node from a source node, the terminal node coupled to thesource node via a direct communications link and a variable redundancydelivery network comprising one or more intermediate storage nodes,storing a given message of the plurality of messages in a first locationin the one or more intermediate storage nodes when the given message hasbeen delivered to the terminal node a first threshold number of times,storing the given message in a second location in the one or moreintermediate storage nodes when the given message has been delivered tothe terminal node a second threshold number of times, determining thatthe given message is to be delivered to the terminal node, in responseto the determination, delivering the given message stored in the one ormore intermediate storage nodes to the terminal node.

Yet other described aspects include a communication system comprising aterminal node, a source node, a direct communications link to delivermessages to the terminal node via the source node, and a variableredundancy delivery network to deliver the messages to the terminalnode, the variable redundancy delivery network comprising one or moreintermediate storage nodes redundantly storing the messages withvariable redundancy in multiple locations based on a non-uniformprobability density of the messages.

BRIEF DESCRIPTION OF THE DRAWINGS

A further understanding of the nature and advantages of embodiments ofthe present disclosure may be realized by reference to the followingdrawings. In the appended figures, similar components or features mayhave the same reference label. Further, various components of the sametype may be distinguished by following the reference label by a dash anda second label that distinguishes among the similar components. If onlythe first reference label is used in the specification, the descriptionis applicable to any one of the similar components having the same firstreference label irrespective of the second reference label.

FIG. 1 shows an example communications environment for capacityenhancement of a direct communication link in accordance with variousaspects of the disclosure.

FIG. 2 shows one example of a cumulative distribution function of anexample message library, in accordance with various aspects of thedisclosure.

FIG. 3 shows a flow diagram of an example message flow for capacityenhancement of network access service in accordance with various aspectsof the disclosure.

FIG. 4 shows a plot of a normalized cumulative distribution function inaccordance with various aspects of the present disclosure.

FIG. 5 shows a plot of example optimized storage policies compared tomessage striping for a variable redundancy delivery network inaccordance with various aspects of the present disclosure.

FIG. 6 shows plots of example variable redundancy storage policies for avariable redundancy delivery network in accordance with various aspectsof the present disclosure.

FIG. 7 shows a flow diagram of an example message flow for capacityenhancement of network access service in accordance with various aspectsof the disclosure.

FIG. 8 shows a diagram of example storage redundancy thresholds forvariable message redundancy in accordance with various aspects of thepresent disclosure.

FIG. 9 shows a block diagram of a variable redundancy delivery networkin accordance with various aspects of the present disclosure.

FIG. 10 shows a block diagram of a variable redundancy manager forcapacity enhancement of a direct communications link in accordance withvarious aspects of the disclosure.

FIG. 11 shows a simplified diagram of an example satellitecommunications system 1100 which may implement capacity enhancement of adirect communication link in accordance with various aspects of thedisclosure.

FIG. 12 shows a flowchart diagram of an example method for capacityenhancement of a communications system in accordance with variousaspects of the disclosure.

FIG. 13 shows a diagram of a design environment for designing a variableredundancy delivery network in accordance with various aspects of thepresent disclosure.

DETAILED DESCRIPTION

The described feature generally relate to capacity enhancement of adirect communication link serving multiple users using a variableredundancy delivery network. In some examples, an estimated informationrate for serving the multiple users may be partitioned into a firstinformation rate provided via the direct communication link and a secondinformation rate to be provided via the variable redundancy deliverynetwork. The variable redundancy delivery network may implement astorage policy that may include various redundancy coding schemes and avariable message redundancy policy that may be determined based on anon-uniform probability distribution of messages requested by themultiple users. In some embodiments, the variable message redundancypolicy may be an optimal policy or a heuristically determined policy.One or more parameters of the variable redundancy delivery network maybe selected to provide the second information rate based on thenon-uniform probability density of messages requested by the users.

The variable redundancy delivery network may include multipleintermediate storage nodes in a non-redundant disk array configuration.For example, each intermediate storage node may be a logical storageunit and may be or include a storage media device (e.g., storage drive,etc.). Capacity and reliability of the storage media devices may betraded off to provide the second information rate. For example, thestorage media devices may be a relatively low reliability storage device(e.g., rotating disk storage media) having a relatively higher storagecapacity. Additionally or alternatively, some or all intermediatestorage nodes may include solid state storage media, which typically hashigher reliability but lower storage capacity per device. The variableredundancy delivery network may dynamically optimize the storage policybased on changes in the distribution of requested messages or changes intotal storage or number of nodes (e.g., due to node failure, etc.) tooptimize the second information rate.

This description provides examples, and is not intended to limit thescope, applicability or configuration of embodiments of the principlesdescribed herein. Rather, the ensuing description will provide thoseskilled in the art with an enabling description for implementingembodiments of the principles described herein. Various changes may bemade in the function and arrangement of elements.

Thus, various embodiments may omit, substitute, or add variousprocedures or components as appropriate. For instance, it should beappreciated that the methods may be performed in an order different thanthat described, and that various steps may be added, omitted orcombined. Also, aspects and elements described with respect to certainembodiments may be combined in various other embodiments. It should alsobe appreciated that the following systems, methods, devices, andsoftware may individually or collectively be components of a largersystem, wherein other procedures may take precedence over or otherwisemodify their application.

The rise in consumption of network multimedia content such as systemsproviding audio and video on demand (AVOD) and use of audio and videosharing services (e.g., YouTube, Vine, etc.) has dramatically increasedconsumer bandwidth usage. In addition, users increasingly expect ahigh-quality broadband experience while travelling. For example, thereis a growing demand for network access service during air travel, andthe desire to be able to access network multimedia content on airplanesand in other mobile environments has created challenges in providingsufficient bandwidth for users over bandwidth-limited wireless networks.

In various mobile environments, multiple users may be provided networkaccess service via a shared communication link. For example, users mayconnect their communication devices to a wireless local area network(WLAN), which routes data communications to other networks (e.g., theInternet) via the shared communication link. The shared communicationlink may be a wireless link (e.g., cellular link, satellitecommunications link, etc.), and may have limited communicationbandwidth. For example, while the resources (e.g., frequency, time,etc.) of a wireless network may be flexibly applied for multiple users,the overall capacity of the network may be limited, and congestion canoccur when users request more resources at a particular time than thenetwork can support. Increasing bandwidth for wireless communicationssystems is expensive and sometimes additional usable spectrum isunavailable. Therefore, providing a high-quality network accessexperience at a reasonable cost in mobile environments presents manychallenges.

FIG. 1 shows an example communications environment 100 for capacityenhancement of a direct communication link in accordance with variousaspects of the disclosure. The communications environment 100 includes adirect communication link 110-a used for providing network accessservice for multiple communication devices 115 (represented as aterminal node 140-a) of a mobile environment 105-a via a network gatewaydevice 150-a. The communication devices 115 may be mobile devices (e.g.,smartphones, laptops, tablets, netbooks, and the like) and maycommunicate with the network gateway device 150-a via communicationlinks 125. Communication links 125 may be, for example, part of a localnetwork such as a WLAN. The communication devices 115 may be userdevices located in mobile environment 105-a, which also includes thenetwork gateway device 150-a.

The direct communication link 110-a may be a wireless communication linkbetween the network gateway device 150-a located on the mobileenvironment 105-a and one or more networks 120-a, which may include anysuitable public or private networks and may be connected to othercommunications networks such as the Internet, telephony networks (e.g.,Public Switched Telephone Network (PSTN), etc.), and the like. Theinformation rate for servicing the communication devices 115 may dependon the number of communication devices 115 in the mobile environment105-a and types of traffic requested by the users, and may vary overtime. For example, the network traffic (also referred to herein as“messages”) requested by the communication devices 115 may include a mixof web traffic, streaming traffic, and other types of traffic. The typesof network traffic that generally consume the most communicationresources are file sharing and video communications (e.g., videoconferencing, video streaming, etc.) with some estimates indicating thatas much as 50% of all Internet traffic is video streaming traffic.

The probability distribution of requested content tends to benon-uniform. For example, the same streaming traffic may be requested bymultiple users at different points in time, or may be shared acrossmultiple users if they request broadcast or multicast streaming traffic.FIG. 2 shows a plot 200 of a cumulative distribution function (CDF) 205for an example message library, in accordance with various aspects ofthe disclosure. A message in the message library may be some or all of apiece of content. For example, a message may be some or all of anaudio-video item (e.g., a movie, television show, etc.), an audio-onlyitem (e.g., a song, etc.), or any other type of network traffic datathat can be stored locally to a mobile environment (e.g., mobileenvironment 105-a of FIG. 1, etc.) and subsequently provided to aterminal node (e.g., one or more communication devices 115 of FIG. 1,etc.) in response to additional requests for the message. CDF 205 mayillustrate, for example, the cumulative message requests as a functionof a message index shown as a percentage of unique messages. CDF 205 isapproximately log-linear, with 20% of the unique messages accounting forapproximately 85% of the message requests. Similarly, content such as“viral” videos may be repeatedly requested by many different userswithin a span of days or even hours.

Returning to FIG. 1, the capacity of direct communication link 110-a maybe flexible to meet the information rate demands of the communicationdevices 115 represented by terminal node 140-a. However, the informationrate provided by direct communication link 110-a may have limits givenby system bandwidth, hardware limitations (e.g., power constraints), oroverall system capacity. For example, communications environment 100 maybe part of a communications system, which may have a limited overallinformation rate capacity. In addition, the incremental cost for theinformation rate provided over direct communication link 110-a may berelatively high. While it may be possible to restrict some types oftraffic (e.g., high definition video, etc.), this may degrade thenetwork access experience for various users. These and other issues ofproviding network access service in mobile environments typically resultin high cost of service, a reduced quality user experience, or both.

One way to increase the effective information rate of directcommunication link 110-a is to store some content locally to the mobileenvironment 105-a. For example, when a communication device 115 makesrequests for a set of messages from network 120-a via the directcommunication link 110-a, the messages can also be stored in a storagesystem connected to network gateway device 150-a. If the same set ofmessages are then later requested by other communication devices 115,the stored messages can be provided from the local storage instead ofbeing re-sent over the direct communication link 110-a. The amount ofeffective information rate enhancement provided by locally storedcontent depends on the amount of storage, the reliability of the storagesystem, and the probability distribution of requested messages. Toprovide a significant effective increase in information rate (e.g., 10%or higher) provided to the communication devices 115, the local storagecapacity required may be large. For example, to cover a substantialpercentage of streaming traffic (e.g., 10-50%), storage capacities inthe 10-200 Terabyte (TB) range may be necessary.

Different types of storage media may have different trade-offs betweenstorage capacity and reliability. For example, a rotating disk storagedevice (commonly known as a hard disk drive (HDD)) uses a rotatingmagnetic media platter with a read and write head that operates over themagnetic surface to detect and modify magnetization of the magneticmedium on the platter. Rotating disk storage devices have relativelyhigh storage capacity while providing data access in any desired order(e.g., random access). A solid state drive (SSD) is a data storagedevice that uses electronic non-volatile storage media (e.g., NAND flashmemory, magnetoresistive random-access memory (MRAM), etc.) topersistently store data (maintain data when powered off). Hybrid drivesare devices that include both SSD and HDD technology.

In some cases, the mobile environment 105-a may be subject tosubstantial shock and vibration, as well as other extreme environmentalconditions. For example, the mobile environment 105-a may be anaircraft, which may suffer from vibration due to engines and hydraulicsystems, and may encounter turbulence that results in significantgravitational forces (g-forces) seen by components on the aircraft.Other mobile environments such as ships and trains may also seesignificant shock or vibration occur intermittently. Compared with HDDs,SSDs are typically more resistant to physical shock, run silently, havelower access time, and less latency. Because HDDs have read/write headsthat float above spinning platters, HDDs may be susceptible to shock andvibration, as well as other mechanical failure mechanisms. In contrast,mechanical failure rates for SSDs are generally low because SSDs have nomoving parts. However, SSDs may have a limited number of write cycles(or erase cycles), which may affect life-time of the drive in certainapplications.

Higher cost is a substantial drawback to the use of SSDs for largercapacity storage applications. For example, consumer-grade SSDs may beapproximately 10 times more expensive per unit of storage thanconsumer-grade HDDs. Although prices for SSDs are declining, theconsumer price for SSDs may currently be in the range of $500-$1500 perTB of storage (depending on drive storage size) compared toapproximately $40-80 per TB for HDDs. Additionally, the availablestorage capacity in a single HDD device is generally larger than thatavailable for a single SSD device. For example, the largest available3.5″ consumer HDDs may be in the 8-12 TB range, while the largestavailable SSDs, although a smaller form factor, may be in the 1-2 TBrange. Thus, many more SSD devices may be necessary to provide a giventotal storage size.

To create a storage system using multiple drive devices, datavirtualization techniques such as redundant array of independent disks(RAID) may be used to combine multiple drive devices into a singlelogical unit that stores data using redundancy techniques. A commonlyused RAID technique is data mirroring where a set of data is written totwo or more drive devices, and the data is available as long as at leastone drive device where the data is stored is functional. Another RAIDtechnique for use with more than two drive devices is striping withdistributed parity information. Striping with distributed parityinformation may provide higher effective storage capacity for a giventotal storage size but is only tolerant of failure of a single drivedevice. Fault tolerance may be increased by increasing the parityinformation (e.g., double parity information for fault tolerance of upto two failed drives, etc.), at the expense of effective capacity.

In embodiments, the communications environment 100 is configured toincrease the effective capacity between the network 120 and thecommunication devices 115 by using a variable redundancy deliverynetwork (VRDN) 130-a to store messages for subsequent delivery tocommunication devices 115. The VRDN 130-a includes intermediate storagenodes (ISNs) 135-a (e.g., ISNs 135-a-1, 135-a-2, . . . , 135-a-n), whichmay each include a storage device (e.g., HDD, SSD, Hybrid drive, etc.).In some examples, a system may include different types of ISNs 135-a(e.g., HDD, SSD, hybrid drives, etc.).

The VRDN 130-a may provide control of message flow for messagesrequested by the terminal node 140-a (e.g., communication devices 115,etc.) via the network gateway device 150-a. The VRDN 130-a may includevariable redundancy manager (VRM) 160-a, which may manage redundancy ofmessages on VRDN 130-a based on a storage policy. The storage policy maybe based on a non-uniform distribution of message requests (e.g.,frequency of request of the messages). In some examples, VRDN 130-a isconnected with the network gateway device 150-a via a local network155-a (e.g., local area network (LAN), storage area network (SAN),etc.). Each ISN 135-a may present itself on local network 155-a as aseparate logical storage unit (e.g., without internal redundancy). Inother examples, VRM 160-a may be part of VRDN 130-a and may communicatewith network gateway device 150-a via a connection 155-a (e.g., LAN,SAN, etc.).

FIG. 3 shows a flow diagram 300 of an example message flow for capacityenhancement of network access service in accordance with various aspectsof the disclosure. Flow diagram 300 illustrates message flow between anetwork 120-b, network gateway device 150-b, VRDN 130-b, and a terminalnode 140-b, which may be, for example, the network 120-a, networkgateway device 150-a, VRDN 130-a, and terminal node 140-a of FIG. 1. Theterminal node 140-b may be provided network access service to network120-b via network gateway device 150-b, which may have a directcommunication link 110-b to network 120-b. Network gateway device 150-bmay be connected to VRDN 130-b. Terminal node 140-b (e.g., user devices115 of FIG. 1) may be connected to network gateway device 150-b vialinks 225 (e.g., LAN, WLAN, etc.). Optionally, one or more devices ofterminal node 140-b may be connected directly to VRDN 130-b via links230 (e.g., where VRDN is a node of a local network coupled with networkgateway device 150-b and the devices of terminal node 140-b). Flowdiagram 200 may illustrate, for example, message flow in thecommunications environment 100 of FIG. 1.

VRDN 130-b may be understood as providing an indirect communication linkthat increases the apparent capacity of direct communication link 110-b.Thus, terminal node 140-b may receive messages from network 120-b viathe direct communications link 110-b, or via an indirect communicationlink from VRDN 130-b providing stored messages that may have previouslybeen received via direct communication link 110-b. If the physical linkcapacity of links 225 and/or 230 are large with respect to the physicalcapacity of direct communication link 110-b, the effective data rate ofthe indirect communication link provided by VRDN 130-b may be dependenton the probability that VRDN 130-b has a given message requested byterminal node 140-b.

In flow diagram 300, a request 305 for message A may be sent by terminalnode 140-b. Message A may be, for example, a file or object that is partof a video stream (e.g., HTTP live streaming (HLS) file, etc.) requestedfrom a content server of network 120-b by a communication device 115 inthe communications environment 100 of FIG. 1. The request 305 may be thefirst request for message A from a communication device 115. Thus,message A may not be stored in VRDN 130-b and network gateway device150-b may send the request 305 to network 120-b.

The network 120-b may respond 310 with message A, which may be deliveredto the terminal node 140-b. The message A may also be stored in VRDN130-b. In some cases, whether message A is stored in VRDN 130-b maydepend on the type of the message (e.g., determining that message A is atype of message for which a local copy can be delivered in response to asubsequent request, etc.).

One or more subsequent requests 315 for message A may be sent by theterminal node 140-b (e.g., by other communication devices 115 in thecommunications environment 100 of FIG. 1, etc.). Because message A isstored in VRDN 130-b, the content of message A may be delivered 340 tothe terminal node 140-b without sending the message itself over thedirect communications link 110-b. In some cases, network gateway device150-b may request 320 an index to message A and network 120-b may sendindex 335 in response to the request 320, which may correspond to alocation of message A in VRDN 130-b. Alternatively, NGD 150-b mayintercept one or more of the requests 315 and VRDN 130-b may deliver 340message A to terminal node 140-b in response to the requests withoutreceiving index 335 for each request of message A.

VRDN 130-b may determine message redundancy at block 345 for message Abased on the requests 315. In embodiments, the VRDN 130-b may includemultiple (e.g., N) ISNs 135-a and storage of message A in one or more ofthe ISNs 135-a may be according to a storage policy that may bedetermined based on a statistical distribution of messages. For example,a probability density function (PDF) represented by ρ(x) may beunderstood as the probability that a given message will be requestedaccording to message index x, if requested messages are orderedaccording to frequency of request, generally decreases with increasingx. The CDF that corresponds to ρ(x) may be given by F(x).

The storage policy may include a redundancy coding scheme (e.g., messagereplication, parity codes, Reed-Solomon codes, etc.) and a messageredundancy policy u that represents the redundancy as a function ofmessage index x. A mapping function g(u) may describe the total storageneeded for a given redundancy level for a given redundancy codingscheme. For repetition coding (e.g., replication of a message acrossISNs), the message redundancy policy u may be understood as the numberof times the message is stored and the mapping function g(u) may beunity. Determining message redundancy at block 345 may includedetermining a redundancy for message A based on the storage policy.

Returning to FIG. 1, it may be desired to provide a given informationrate R₀ to the terminal node 140-a for a communication service. For amulti-user environment such as a communication service for passengers ona commercial aircraft, R₀ may be estimated as:R ₀ =N _(P) ·TR·R _(U)  (1)where:

-   -   N_(P) is the number of passengers;    -   TR is the take rate of the communication service; and    -   R_(U) is the estimated information rate per user.

The estimated information rate R₀ may be divided into R₁, an informationrate of the direct communication link 110-a, and R₂, an information ratefrom the VRDN 130-a, such that:R ₀ =R ₁ +R ₂  (2)Or:R ₂ =R ₀ ·R ₁  (3)

The message availability from the VRDN depends on the percentage ofunique messages stored in the VRDN, the message PDF ρ(x), and how thosemessages are stored. In some aspects, the information rate from the VRDNR₂ may be understood as a function of the minimum message availabilityfrom the VRDN P_(I) ^(min) to provide a given information rate R₀, suchthat:

$\begin{matrix}{P_{I}^{\min} = \frac{R_{2}}{R_{0}}} & (4)\end{matrix}$

The probability of message availability from the VRDN 130-a P_(I) isdependent on the message PDF ρ(x) and message redundancy policy u, andcan be given by:P _(I)(u)=∫₀ ^(∞)ρ(x)ϕ_(u)(x)dx  (5)where:

-   -   ϕ_(u)(x) is the message delivery reliability (i.e., probability        that message x can be delivered from a given storage system        having a given message redundancy policy u).

The message delivery reliability ϕ_(u)(x) for a given message x isdependent on whether the message has been stored, how the message isstored, and a message retrieval reliability M_(rr). Whether the messagehas been stored and how the message is stored depend on the physicalparameters of the storage system (e.g., total storage size, number ofnodes) and the storage policy.

Message retrieval reliability M_(rr) is defined as the probability overa given time period (e.g., a year) that a given message stored in agiven individual storage node can be accessed (successfully read out).The message retrieval reliability depends on the drive failure rate overthe given time period of the given individual storage node, and furtherdepends on the probability of an unrecoverable read error (URE) over thegiven time period of the given message stored in the given individualstorage node. Generally, the drive failure rate and the probability ofURE are independent, although this may not be true in all cases.

The drive failure rate is the rate at which the given individual storagenode malfunctions and thus none of the stored messages can be accessed.The drive failure rate is dependent on drive characteristics (e.g., SSD,HDD, etc.) and possibly the operational environment. A URE is the lossof any stored message due to uncorrectable bit error(s) and/or temporaryinaccessibility of data. For example, an intermediate storage node mayenter a protected mode if adverse environmental conditions are detectedand the messages stored on the node may be temporarily unavailable. AURE depends on drive characteristics and the error correction coding (ifany) that is used for storing messages in the given individual storagenode.

If the total storage size of the VRDN is L, the following constraintholds:L=∫ ₀ ^(X) g(u(x))dx  (6)where:

-   -   u(x) is the message redundancy policy for a given storage        policy;    -   g(n) is a function of the redundancy coding scheme used for the        given storage policy and accounts for possible redundancy coding        schemes that are not direct replication; and    -   X is the index of the lowest frequency message stored (i.e., all        messages in the range [0;X] are stored at least once with the        messages sorted by decreasing frequency).

The storage policy may be selected using a variety of techniques. Forexample, the redundancy coding scheme used for the storage policy may beselected based on system attributes (e.g., processing capabilities,expected URE types, etc.). The message redundancy policy u may be afixed message redundancy policy. For example, the message redundancypolicy u may be predetermined according to an estimated message PDFρ(x), and may be independent of the parameters of the VRDN.Alternatively, the message redundancy policy u may be determined basedon various system parameters for the VRDN (e.g., total storage size,number of nodes, message retrieval reliability, etc.).

In some examples, message redundancy policy u is determined usingoptimization techniques. For example, expressions 5 and 6 can be seen asan optimal control problem satisfying the conditions for maximizing anobjective function using Pontryagin's Maximum Principle with freeterminal condition (e.g., X is not explicitly fixed). The optimizationproblem may be understood as finding a message redundancy policy u*thatmaximizes P_(I), given ϕ_(u)(x), ρ(x), L, and g(n). Or, restated:

$\begin{matrix}{u^{*} = {\max\limits_{u}\lbrack {\int_{0}^{X}{{\rho(x)}{\phi_{u}(x)}{dx}}} \rbrack}} & (7) \\{{s.t.\mspace{11mu} L} = {\int_{0}^{X}{{g( {u(x)} )}{dx}}}} & (8)\end{matrix}$Expressions 7 and 8 may be solved to find the optimal message redundancypolicy u* using known techniques (e.g., Ross-Fahroo pseudo-spectralmethods, shooting methods, etc.).

For designing a VRDN 130 to provide a desired information rate R₂ givena known or estimated CDF F(x) and overall information rate R₀, one ormore parameters of the VRDN 130 (e.g., number of storage nodes N, typesof storage nodes, total storage L, storage policy, etc.) may be selectedand the probability of message availability from the VRDN P_(I)determined. For the given system parameters, it may be determined if theprobability of message availability from the VRDN P_(I) provides thedesired information rate R₂ for the system. The system parameters of theVRDN 130 may then be iteratively adapted until the desired informationrate R₂ can be achieved. The iteration may be performed over the systemdesign variables (e.g., storage policy, number of storage nodes N, typeof storage node, total storage L, etc.) to achieve the desiredinformation rate R₂ or to satisfy other constraints (e.g., size, weight,cost, etc.). In some examples, the storage policy may be adapted forvarious iteration steps. For example, the message redundancy policy u(x)may be optimized at each of a number of iteration steps (e.g., for giventypes of ISNs, number of storage nodes N, and total storage L, etc.).

FIG. 4 shows a plot 400 of a normalized cumulative distribution functionin accordance with various aspects of the present disclosure. In theexample normalized message CDF 410 of FIG. 4, the message distributionis represented using a heavy-tailed Pareto distribution parameterized byvalues β, ϵ. For example, the message distribution may be given by:

$\begin{matrix}{{F(x)} = {{\int_{0}^{x}{{\rho(s)}{ds}}} = {1 - ( \frac{\epsilon}{1 + \epsilon} )^{\beta}}}} & (9)\end{matrix}$

We assume that messages are ordered in decreasing (probabilistic)frequency, so expression 9 couples the quantity of unique messages(i.e., x) with the proportion of total requested messages that arewithin the quantity x. Without loss of generality, we may normalize themessage CDF F(x) such that F(1)=½. In addition, the size of the messagesmay be normalized to a selected message unit size (e.g., larger messagesmay be represented by multiple normalized messages, etc.). Thus, FIG. 4illustrates the message CDF F(x) shown as a function of the normalizedmessage index (NMI) x. This yields the constraint:

$\begin{matrix}{\epsilon = \frac{( {1\text{/}2} )^{1/\beta}}{1 - {1\text{/}2_{\;}^{1/B}}}} & (10)\end{matrix}$Under this scaling, messages in the range [0; 1] would account for halfof the total messages expected over a given time period, as shown byline 415. In some aspects, a heavy-tailed distribution has propertiesthat reflect realistic scenarios. In particular, for heavy taileddistributions it is infeasible to store nearly all messages due to thewide variety of messages that are possible. Thus, there are diminishingreturns for larger storage capacity. In the example illustrated bymessage CDF 410, β=5.

The message CDF shown in FIG. 4 is only an example of possibledistributions, a message distribution for a particular environment canbe estimated or curve-fit (e.g., based on message requests, etc.). Forexample, empirical data for message requests may be parameter-fit usinglog-linear, Pareto, or other statistical models to determine a messageCDF for a particular environment.

In some examples, the VRDN may use message replication for the messageredundancy coding scheme. For message replication in a VRDN having Nstorage nodes, message redundancy policy u maps each message index x toan integer between 0 and N. Assuming that the ways in which a givenmessage x is stored on u(x) nodes are equally probable, and each nodehas a message retrieval reliability M_(rr) expressed as the probabilitythat a message stored at a given node can be successfully read out(e.g., including the possibility of drive failures and UREs, etc.), theprobability that message x can be retrieved from storage is given by:

$\begin{matrix}{{\phi_{u}(x)} = {\sum\limits_{i = 1}^{u{(x)}}{\begin{pmatrix}{u(x)} \\i\end{pmatrix}{M_{rr}^{i}( {1 - M_{rr}} )}^{{u{(x)}} - i}}}} & (11)\end{matrix}$

The VRDN parameters (e.g., number of storage nodes N, types of storagenodes, total storage L, etc.) may be iteratively adapted until a desiredinformation rate R₂ can be provided. For each iteration, the optimalmessage redundancy policy u(x) may be determined by solution of theoptimization determined by expressions 7 and 8 as discussed above, withthe message delivery reliability ϕ_(u)(x) given by expression 11.

While the techniques for selecting an optimal message redundancy policyu(x) may provide an optimized message availability from the VRDN 130-aP_(I) message redundancy policy u(x) may alternatively be selected basedon simplified or heuristic techniques. For example, the messageredundancy policy u(x) may be determined by a normalized curve fit(e.g., linear, log-linear, polynomial, etc.) of the message PDF ρ(x). Asanother example, heuristic approaches for determining the messageredundancy policy u(x) may include gradient ascent, monte carlo search,simulating annealing, and the like. Heuristic approaches may, forexample, provide a quasi-optimal message redundancy policy u(x) withless computational complexity.

FIG. 5 shows a plot 500 of example optimized storage policies comparedto message striping for a variable redundancy delivery network inaccordance with various aspects of the present disclosure. The curves inplot 500 are shown for a system using replication as the message codingscheme, N=5, and a heavy-tailed Pareto distribution CDF F(x) given inexpression 10 having β=5, with storage sizes normalized such thatF(1)=½. That is, storage of all messages in the range [0; 1] wouldaccount for half of the total messages expected over a given timeperiod.

In plot 500, curve 510 shows the normalized storage size required toachieve a given P_(I) using a uniform message redundancy policy of 3×striping (e.g., replication of messages across nodes) where M_(rr)=0.5.As shown by curve 520, a VRDN using a message redundancy policy u(x)optimized for the example message CDF F(x) and VRDN parameters canprovide up to approximately a 2× increase in the achievable messageavailability P_(I) at some storage sizes.

Curve 515 shows the normalized storage size required to achieve a givenP_(I) using a uniform message redundancy policy of 3× striping whereM_(rr)=0.8. Curve 525 shows that a VRDN using a message redundancypolicy u(x) optimized for the message CDF F(x) and VRDN parameters canprovide greater than a 2× increase in the achievable messageavailability P_(I) through a substantial portion of the range of storagesizes.

FIG. 6 shows plots 600 of example variable message redundancy policiesfor a VRDN in accordance with various aspects of the present disclosure.Plots 600 show optimized message redundancy policies u(x) 620 used forcalculating the message availability P_(I) for storage size L=1 of plot500. As with plot 500, the message axes 605 have been normalized for theheavy-tailed Pareto distribution CDF F(x) given in expression 10 havingβ=5 such that F(1)=½.

As shown by comparison to the 3× striping redundancy scheme 610, theoptimized message redundancy policies u(x) 620 may increase redundancyfor messages having a high probability of being requested (e.g., lowmessage index) while decreasing redundancy for messages having a lowerprobability of being requested, and may have a higher proportion oftotal unique messages that are stored at least once.

The plots in FIGS. 5 and 6 are examples shown with simplified staticsystem parameters such as N=5, and with changes in message redundancyfor a given message having message index x being an integer of themessage size (e.g., message replication). However, other systemparameters and/or redundancy coding schemes may be used. For example,coding or parity schemes may be used to increase redundancy with anyincremental redundancy step size, providing a higher level ofgranularity to the optimized message redundancy policy u(x). For othercoding techniques or system designs, the message delivery reliabilityϕ_(u)(x) and coding storage usage function g(n) may be derived such thatthe probability of message availability from the VRDN P_(I) can bedetermined across the system variable state space according to the abovetechniques. For example, a system may include a combination of types ofstorage (e.g., HDD, SSD, etc.) and may use different coding schemesacross different types of storage.

Optimization of probability of message availability from the VRDN 130-aP_(I) according to the above techniques can be used to determine a totalstorage size L given a number of storage nodes N to provide a targetinformation rate R₂. For example, for a system having N=5 andM_(rr)=0.8, if the target information rate R₂ is approximately 0.33 ofR₀, a total storage size L=10° (based on the normalized message CDF)would be used. Typically, a system may have other constraints on systemvariables. For example, there may be a limit on the storage size T ofeach intermediate storage node. Constraints on various system variablesmay be defined, and techniques may be used to traverse the state spaceof the system design (e.g., gradient ascent, monte carlo search,simulating annealing, etc.) to design a system within overall systemconstraints (e.g., size, weight, cost, etc.).

Once a VRDN has been deployed, it may optimize information rate R₂ basedon current system parameters (e.g., taking into account drive failure orsector failure, etc.) or changes in the message PDF ρ(x). For example,the VRDN 130 may monitor message requests and dynamically update themessage PDF ρ(x) used for determining the message redundancy policyu(x).

FIG. 7 shows a flow diagram 700 of an example message flow for capacityenhancement of network access service in accordance with various aspectsof the disclosure. Flow diagram 700 may illustrate message management ina VRDN 130 of FIG. 1 or 3 for managing message storage and redundancy toprovide capacity enhancement of a direct communications link based on anon-uniform probability distribution of requested messages. Flow diagram700 may illustrate, for example, aspects of message flow 300 forproviding capacity enhancement to a direct communications link 110.

Message flow 700 may begin at block 705, where message flow 700 may waitfor message requests from a terminal node (e.g., communication devices115 of FIG. 1). When a message request is received at block 705 for amessage x, the message flow 700 may proceed to block 715 to determine ifmessage x has already been stored in the VRDN 130 (e.g., with or withoutredundancy).

If, at block 715, it is determined that message x has not been stored,message flow 700 may proceed to block 720 where message x is retrievedvia the direct communications link. If, at block 715, it is determinedthat message x has been stored, message flow 700 may proceed to block725 where message x is retrieved from the VRDN 130. In some cases, themessage has been stored with redundancy in the VRDN 130 and a firstinstance of the message (e.g., stored on a first intermediate storagenode, etc.) is unavailable (e.g., because of drive failure or URE,etc.). A redundant copy or redundant data for the message may beretrieved from other intermediate storage node. At blocks 720 and 725,the message may be delivered to the terminal node (e.g., communicationdevice 115 that requested the message).

At block 730, a message counter c(x) for the message may be incremented(or initialized if the message has not been previously requested) andthe message flow 700 may proceed to block 735 where redundancy for themessage is determined. In some examples, the message counters c(x) maybe based on message requests over a time period (e.g., a month, a year,etc.). Thus, incrementing message counter c(x) at block 730 may includedetermining the message counter value c(x) based on the requests duringthe time period.

Redundancy for the message may be determined at block 735 based on amessage redundancy policy u(x). For example, the message redundancypolicy u(x) may define thresholds for various levels of redundancy andthe message counter c(x) may be compared to the thresholds to determinethe level of redundancy of the message.

FIG. 8 shows a diagram 800 of example storage redundancy thresholds forvariable message redundancy in accordance with various aspects of thepresent disclosure. Diagram 800 may illustrate, for example, storageredundancy thresholds for a message redundancy policy 850 optimizedbased on a known or estimated message CDF according to the techniquesdescribed above.

In the illustrated example, thresholds T₁ 810, T₂ 820, T₃ 830, and T₄840 correspond to increases in message redundancy based on messagerequest rate. Returning to FIG. 7, the message counter c(x) may becompared to thresholds T₁ 810, T₂ 820, T₃ 830, and T₄ 840 to determinethe storage redundancy for message x. For example, the message may notbe stored if the message counter c(x) is less than T₁ 810. As additionalrequests for the message are received, the message may be stored in afirst location when the message counter c(x) is greater than T₁ 810 butless than T₂ 820, and may be stored in a second location when themessage counter is greater than T₂ 820 but less than T₃ 830, and so on.The first location may be on a first intermediate storage node and thesecond location may be on a second intermediate storage node. In theexample shown in diagram 800, the storage redundancy is shown in integervalues (e.g., message replication). As described above, other codingtechniques may be used to provide any level of granularity in messageredundancy.

Additionally or alternatively, the message redundancy policy 850 mayaccount for different reliability characteristics of different storagedevices. For example, a message may be stored on a first intermediatestorage node having a lower reliability characteristic (e.g., HDD, etc.)when the number of requests for the message is below a threshold andstoring the message on a second intermediate storage node having ahigher reliability characteristic (e.g., SSD, etc.) when the number ofrequests reaches the threshold. Storing the message on the secondintermediate storage node may include erasing the message from the firstintermediate storage node.

At block 740, the message flow 700 may determine if there is a change inmessage redundancy for the message. For example, incrementing of themessage counter c(x) at block 730 may result in a change of storageredundancy for the message as determined by one or more thresholds forthe message redundancy policy. Additionally or alternatively, themessage redundancy policy may have been adapted (e.g., optimized for achange in system variables or message CDF, etc.), changing theredundancy for the message. If the message flow 700 determines at block740 that the message redundancy has changed for the message, messageflow 700 may increase or decrease the message redundancy as appropriateat block 745. If the message flow 700 determines that the messageredundancy has not changed, then the message flow may return to block705 to wait for additional message requests.

Although not shown in message flow 700, the message redundancy policyu(x) and/or message coding scheme for messages may be adaptedperiodically or upon occurrence of one or more events. For example, if asystem variable changes (e.g., drive failure, etc.), the messageredundancy policy u(x) may be optimized for the new system variables.Additionally or alternatively, the message counters c(x) may beperiodically updated based on time period of the requests. For example,message counters c(x) may reflect message requests for a rolling timeperiod (e.g., month, year, etc.) and may be periodically (e.g., hourly,daily, etc.) updated based on the number of requests in the rolling timeperiod. Then, the CDF may be updated and the message redundancy policyu(x) adapted for the updated CDF. Message redundancy may be re-evaluatedfor all stored messages based on the new message redundancy policy u(x).

FIG. 9 shows a block diagram 900 of a variable redundancy deliverynetwork 130-c in accordance with various aspects of the presentdisclosure. VRDN 130-c includes a network interface 935, variableredundancy manager 160-b, processor 905, memory 915 (including software(SW)) 920, and ISNs 135-b-1, 135-b-2, . . . , 135-b-n, each of which maycommunicate, directly or indirectly, with one another (e.g., via buses845).

The network interface 935 may communicate bi-directionally, with one ormore networks or devices. For example, the VRDN 130-c may be connectedwith a network gateway device 150 via network interface 935. The networkinterface 935 may include, for example, one or more wired or wirelessinterfaces such as Ethernet, Wi-Fi, Fibre Channel, small computer systeminterface (SCSI), and the like, for communication with other devices(e.g., via a LAN or SAN).

The variable redundancy manager 160-b may illustrate, for example,aspects of variable redundancy manager 160-a as described above withreference to FIG. 1. The variable redundancy manager 160-b may controlredundancy of messages on VRDN 130-c based on frequency of request ofthe messages and a non-uniform distribution of message requests. Forexample, variable redundancy manager 160-b may determine a messageredundancy policy u(x) based on a CDF F(x) or PDF ρ(x) of messages andother system variables of the VRDN 130-c (e.g., number of ISNs 135-b,storage size T of the ISNs 135-b, total storage size L, estimatedmessage retrieval reliability M_(rr), etc.). The variable redundancymanager 160-b may receive message requests (e.g., via network interface935) from a terminal node (e.g., one or more user devices 115, etc.),determine if requested messages are stored in one or more ISNs 135-b,and retrieve stored messages from the ISNs 135-b for delivery to theterminal node (e.g., via network interface 935).

The memory 915 may include random access memory (RAM) and read onlymemory (ROM). The memory 915 may store computer-readable,computer-executable software/firmware code 920 including instructionsthat, when executed, cause the processor 905 to perform variousfunctions described herein (e.g., managing message redundancy, etc.).Additionally or alternatively, the software/firmware code 820 may not bedirectly executable by the processor 905 but cause the processor 905(e.g., when compiled and executed) to perform the functions describedherein. The processor 905 may include an intelligent hardware device,(e.g., a central processing unit (CPU), a microcontroller, anapplication specific integrated circuit (ASIC), etc.).

FIG. 10 shows a block diagram 1000 of a variable redundancy manager160-c for capacity enhancement of a direct communications link inaccordance with various aspects of the disclosure. The variableredundancy manager 160-c may illustrate, for example, aspects of avariable redundancy managers 160 as described above with reference toFIG. 1 or 9. The variable redundancy manager 160-c may include requestprocessor 1010, redundancy manager 1015, and message processor 1030.Each of these components may be in communication with each other,directly or indirectly.

Request processor 1010 may control functions related to receiving andprocessing requests for messages. Request processor 1010 may maintainmessage counters for messages stored in the variable redundancy deliverynetwork 130 and may, for example, determine the distribution (e.g., CDF,PDF, etc.) of message requests.

Redundancy manager 1015 may control message redundancy and message indextracking. Redundancy manager 1015 may include message index manager 1020and storage policy manager 1025. Message index manager 1020 may receivethe message counter for a requested message from request processor 1010and compare the message counter to one or more thresholds T_(X) fordetermining the message redundancy, as described above with reference toFIGS. 7 and 8.

Storage policy manager 1025 may determine a redundancy coding scheme andmessage redundancy policy u(x) for message redundancy based on themessage CDF or PDF and the system parameters (e.g., number of storagenodes, total storage size, message retrieval reliability from individualnodes, etc.). In some examples, the type of message redundancy codingmay vary as a function of message index or number of requests. Forexample, storage policy manager 1025 may use repetition codes, paritycodes, Hamming codes, Reed-Solomon codes, turbo codes, LDPC codes, orother suitable forms of coding. Storage policy manager 1025 maydetermine the code rate for a given message based on the redundancy ratefor the given message. For example, storage policy manager 1025 maydetermine a number of ISNs 135 in which to store a given message for arepetition coding scheme. Message index manager 1020 may maintain thestorage indexes associated with each message for subsequent messageretrieval from an available message location.

Message processor 1030 may perform functions related to storing andretrieving messages from the indexed locations determined by the messageindex manager 1020. For example, message processor 1030 may retrieve anddeliver stored messages to a terminal node. Message processor 1030 maystore a message in a first location (e.g., a first ISN indicated bymessage index manager 1020) based on a redundancy rate for the messagedetermined by the redundancy manager 1015. The redundancy manager 1015may increase the redundancy rate for the message based on the messagebeing provided to the terminal node a number of times greater than asecond threshold (e.g., upon additional requests for the message), andthe message processor 1030 may store the message in a second location(e.g., a second intermediate storage node indicated by message indexmanager 1020).

Message processor 1030 may determine that the message is to be deliveredto the terminal node (e.g., upon requests for the message fromcommunication devices 115, etc.), and may retrieve the message from thefirst or second location and deliver the message to the terminal node.In some cases, message processor 1030 may determine that the firstintermediate storage node is unavailable, and may retrieve the messagefrom the second location (e.g., the second ISN) and deliver the messagestored in the second location to the terminal node. The first ISN may beunavailable due to, for example, a drive failure or other URE.

The components and modules of variable redundancy manager 160-c of FIG.10 may, individually or collectively, be implemented with circuitry(e.g., ASICs, etc.) adapted to perform some or all of the applicablefunctions in hardware. Alternatively, the functions may be performed byone or more other processing units (or cores), on one or more integratedcircuits. In other embodiments, other types of integrated circuits maybe used (e.g., Structured/Platform ASICs, Field Programmable Gate Arrays(FPGAs) and other Semi-Custom ICs), which may be programmed in anymanner known in the art. The functions of each unit may also beimplemented, in whole or in part, with instructions embodied in amemory, formatted to be executed by one or more general orapplication-specific processors.

FIG. 11 shows a simplified diagram of an example satellitecommunications system 1100 which may implement capacity enhancement of adirect communication link in accordance with various aspects of thedisclosure. The satellite communication system 1100 includes a satellite1105 (or multiple satellites 1105), a ground station 1115, a groundstation antenna system 1110, and a network gateway device 150-c.

In operation, the satellite communication system 1100 provides networkaccess service via the network gateway device 150-c to multiplecommunication devices 115 on a mobile platform such as aircraft 1160.For example, the satellite communication system 1100 may provide fortwo-way communications between the network gateway device 150-c and anetwork 120-c via the satellite 1105 and the ground station 1115. Thecommunication devices 115 may be connected to the network gateway device150-c via one or more access points 1165 (e.g., WAPs, etc.).

The satellite or satellites 1105 may include any suitable type ofcommunication satellite. In some examples, some or all of the satellitesmay be in geostationary orbits. In other examples, any appropriate orbit(e.g., medium earth orbit (MEO), low earth orbit (LEO), etc.) forsatellite 1105 may be used. In one embodiment, the satellite 1105operates in a multi-beam mode, transmitting a number (e.g., typically20-150, etc.) of spot beams each directed at a different region of theearth. This can allow coverage of a relatively large geographical areaand frequency re-use within the covered area. Spot beams forcommunication with subscribers may be called service beams while spotbeams for communication with gateways such as ground station 1115 may becalled feeder beams. In embodiments, the service beams are fixedlocation spot beams, meaning that the angular beam width and coveragearea for each service beam does not intentionally vary with time.

The ground station 1115 sends and receives signals to and from thesatellite 1105 via communication link 1140 using the ground stationantenna system 1110. The ground station antenna system 1110 may betwo-way capable and designed with adequate transmit power and receivesensitivity to communicate reliably with the satellite 1105. The groundstation 1115 is connected to the one or more networks 120-c, which maybe the networks 120 discussed with reference to FIG. 1 or 3.

The network gateway device 150-c may use an antenna 1170 to communicatesignals with the satellite 1105 via the communication link 1155. Theantenna 1170 may be mounted to an elevation and azimuth gimbal whichpoints the antenna 1170 (e.g., actively tracking) at satellite 1105. Thesatellite communications system 1100 may operate in the InternationalTelecommunications Union (ITU) Ku, K, or Ka-bands, for example from 17to 31 Giga-Hertz (GHz). Alternatively, satellite communications system1100 may operate in other frequency bands such as C-band, X-band,S-band, L-band, and the like. As illustrated in FIG. 11, network gatewaydevice 150-c and antenna 1170 are mounted on an aircraft 1160. However,network gateway device 150-c and antenna 1170 may be used in otherapplications besides onboard the aircraft 1160, such as onboard boats,vehicles, or a stationary location where network access service isdesired (e.g., a business, a school, etc.), in some cases.

The satellite communications system 1100 may also include one or moresubscriber terminals 1130, which may also be provided network accessservice via satellite 1105 and ground station 1115. Each subscriberterminal 1130 is located within at least one service beam and is capableof two-way communication with the satellite 1105 via an antenna 1125.Each subscriber terminal 1130 may be connected with (e.g., may providenetwork access service for) one or more customer devices 1135 (e.g.,desktop computers, laptops, set-top boxes, smartphones, tablets,Internet-enabled televisions, and the like). These customer devices 1135may also be known as customer premises equipment (CPE).

Typically, satellite communications system 1100 may have a fixedcapacity based on a system bandwidth and a number of spot beams forfrequency re-use. While that capacity may be allocated to subscriberterminals 1130 and users associated with communication devices 115 in avariety of ways, it may not always be possible to provide a high datarate to all subscriber terminals 1130 and communication devices 115 atthe same time via signals transmitted over the communication links 1150and 1155, respectively.

In embodiments, the satellite system 1100 is configured to increase aneffective information rate provided to communication devices 115 using aVRDN 130-c as described above. The VRDN 130-c may include multipleintermediate storage nodes 135 (e.g., intermediate storage nodes135-c-1, 135-c-2, 135-c-n, etc.) and variable redundancy manager 160-d.Variable redundancy manager 160-d may control redundancy of messages onVRDN 130-d based on frequency of request of the messages and anon-uniform distribution of message requests. For example, variableredundancy manager 160-d may determine a message redundancy codingscheme and/or message redundancy policy u(x) based on a message CDF F(x)or message PDF ρ(x) and other system variables of the VRDN 130-d (e.g.,number of ISNs 135-c, storage size T of the ISNs 135-c, total storagesize L, message retrieval reliability M_(rr), etc.). The variableredundancy manager 160-c may receive message requests (e.g., via networkinterface network gateway device 150-c) from a terminal node (e.g., oneor more user devices 115, etc.), determine if requested messages arestored in one or more ISNs 135-c, and retrieve stored messages from theISNs 135-c for delivery to the terminal node (e.g., via networkinterface network gateway device 150-c). The VRDN 130-d may be connectedto the network gateway device 150-c via a local network 155-c (e.g.,LAN, SAN, etc.). In alternative embodiments, the variable redundancymanager 160-d may be a component of the network gateway device 150-c.

Thus, the effective communication rate to the communication devices 115may be given as R₀=R₁+R₂, where R₁ is the information rate of a directlink (e.g., satellite communications link 1155) and R₂ is theinformation rate provided by the VRDN 130-d via indirect links (e.g.,via network gateway device 150-c and/or AP 1165).

One or more parameters of the VRDN 130-d may be selected to provide theinformation rate R₂. The one or more parameters may include, forexample, reliability characteristics of the one or more intermediatestorage nodes 135-c, a storage size of the one or more intermediatestorage nodes 135-c, a number of the one or more intermediate storagenodes 135-c, a message redundancy coding scheme, and a messageredundancy policy u(x) (i.e., redundancy of storage of messages in theone or more intermediate storage nodes 135-c). The one or moreparameters may be determined based on an estimated information rate R₀from the network 120-c to the communication devices 115 serviced via thenetwork gateway device 150-c, a non-uniform probability density of themessages (e.g., CDF F(x) and/or PDF ρ(x)), or a number of usersaccessing a communication service provided via the network gatewaydevice 150-c.

Determining the reliability characteristics of the one or moreintermediate storage nodes 135-c may include determining a type ofstorage (e.g., HDD, SSD, etc.) for each of the intermediate storagenodes 135-c. The storage types for different intermediate storage nodes135-c may be different. For example, VRDN 130-d may include some highreliability storage intermediate storage nodes 135-c (e.g., SSD storagedevices) and some lower reliability storage (e.g., HDD storage devices)intermediate storage nodes 135-c. In some examples, a message may beinitially (e.g., upon a first request or a number of requests greaterthan a first threshold) stored in the lower reliability storageintermediate storage nodes 135-d. If the number of requests for themessage increases (e.g., above a second threshold, etc.), the messagemay be stored in the a high reliability storage intermediate storagenode 135-c. The instances of the message in the lower reliabilitystorage intermediate storage nodes 135-c may be erased upon storing themessage in the high reliability storage intermediate storage node 135-c.

Determining a storage size and/or number for each of the intermediatestorage nodes 135-c may be based, for example, on the library size M,the non-uniform probability density of the messages, a number of users(e.g., communication devices 115) being provided a communication servicevia the network gateway device 150-c, and/or the information rate R′.

Determining the redundancy of storage may include calculating one ormore redundancy thresholds T_(X) for increasing redundancy based on thenon-uniform probability density of the messages. For example, theredundancy thresholds T_(X) may be determined to match the redundancy tothe non-uniform probability density of the messages (e.g., based onoptimization or heuristic techniques as discussed above, etc.).

FIG. 12 shows a flowchart diagram of an example method 1200 for capacityenhancement of a communications system in accordance with variousaspects of the disclosure. The communications system may include aterminal node coupled to a source node via a direct communications linkand via a variable redundancy delivery network comprising one or moreintermediate storage nodes. The direct communications link may be, forexample, a satellite communication link between the source node and theterminal node as illustrated in FIG. 11.

At block 1205 of method 1200, an estimated information rate R₀ from thesource node to the terminal node may be determined. The estimatedinformation rate R₀ may be determined, for example, based on a number ofusers accessing a communication service provided by the source node viathe terminal node (e.g., number of seats on a plane, etc.) andstatistical information relevant to user information rate (e.g., averagedata rate, peak data rate, etc.).

At block 1210, the estimated information rate R₀ may be partitioned intoa first information rate R₁ for the direct communications link and asecond information rate R₂ for the variable redundancy delivery network.The first information rate may be based on a channel capacity of thedirect communications link.

At block 1215, one or more parameters of the variable redundancydelivery network may be initialized. The one or more parameters mayinclude, for example, reliability characteristics of intermediatestorage nodes of the variable redundancy delivery network, a storagesize of the intermediate storage nodes, and a number of the intermediatestorage nodes. In some examples, some of the parameters may bepredetermined or empirically determined for a selected systemarchitecture (e.g., reliability characteristics of the intermediatestorage nodes, message library size, estimated number of users, etc.).Block 1215 may correspond to selecting an initial system model estimatedto provide the second information rate R₂. In some examples, one or moreof the parameters may be selected based on component availability (e.g.,storage size of the intermediate storage nodes, etc.). In some examples,initialization of the one or more parameters may take the form ofselecting multiple system models with different sets of parameters(e.g., a first system model using HDDs for the intermediate storagenodes, a second system model using SSDs, a third system model using amix of HDDs and SSDs, etc.).

At block 1220, a storage policy may be determined for the system model.The storage policy may include a message redundancy coding scheme and amessage redundancy policy u(x), and may be determined based on anon-uniform probability density of the messages (e.g., estimated messageCDF F(x) and/or message PDF ρ(x)). In some examples, the messageredundancy coding scheme and a message redundancy policy u(x) may befixed (e.g., independent of the system parameters of the VRDN, etc.). Insome examples, the message redundancy policy u(x) may be an optimalmessage redundancy policy determined according to the techniquesdescribed above. In other examples, the message redundancy policy u(x)may be a simplified or heuristically determined policy. For example, themessage redundancy policy u(x) may be determined by a normalized curvefit (e.g., linear, log-linear, polynomial) of the message PDF ρ(x).

At block 1225, the probability of message availability P_(I) may bedetermined for the system model(s). For example, the message deliveryreliability ϕ_(u)(x) may be determined based on the message redundancypolicy u(x) and other system parameters (e.g., message redundancy codingscheme, number of storage nodes N, total storage L, message retrievalreliability M_(rr) for individual storage nodes, etc.) and theprobability of message availability P_(I) may be determined for themessage PDF ρ(x), message delivery reliability ϕ_(u)(x), and codingscheme function g(n) as described above.

At block 1230, it may be determined if the probability of messageavailability P_(I) for one or more of the system model(s) satisfies thecondition P_(I)≥R₂/R₀ for given system target values for R₂ and R₀. If,at block 1230, the probability of message availability P_(I) does notsatisfy the condition, one or more parameters of the VRDN may bemodified at block 1235. For example, more reliable storage devices(e.g., a different type or model of intermediate storage node) may beselected, a different number of intermediate storage nodes may beselected, a different storage size for the intermediate storage nodesmay be selected, or a different message redundancy coding scheme may beselected at block 1235.

Where, at block 1245, the storage policy is selected as a fixed storagepolicy (e.g., independent of VRDN parameters, etc.), the probability ofmessage availability P_(I) may then be determined for the new systemmodel at block 1225 and compared against the design condition at block1230. Where it is determined that the storage policy is dependent on theVRDN parameters at block 1245 (e.g., optimized message redundancypolicy, heuristically determined message redundancy policy, etc.), themessage redundancy policy u(x) may then be determined for the new systemmodel at block 1220 prior to determination of the probability of messageavailability P_(I) at block 1225. In some cases, multiple system modelsmay be generated at block 1235 by modifying one or more parameters indifferent ways to compare system options. For example, system modelshaving the same total storage size L but different numbers ofintermediate storage nodes may be generated at block 1235 based onavailable component sizes (e.g., twenty 1 TB drives vs. ten 2 TB drives,etc.). Various techniques may be used to traverse the state space of thesystem design at block 1235 (e.g., gradient ascent, monte carlo,simulating annealing, etc.).

When one or more system models satisfy the condition P_(I)≥R₂/R₀ for agiven desired R₂ and estimated R₀ at block 1230, the system parametersmay be determined and components selected for the VRDN at block 1240. Insome cases, multiple system models may satisfy the condition at block1230. In such a case, the system component selection for the VRDN atblock 1240 may be based on an additional metric (e.g., selected tominimize a cost metric, selected based on system size or weightconstraints, etc.).

FIG. 13 shows a diagram 1300 of a design environment 1305 for designinga variable redundancy delivery network in accordance with variousaspects of the present disclosure. The design environment 1305 includesVRDN state space processor 1380, message delivery processor 1320, memory1315, I/O devices 1310, and communications module 1335, which each maybe in communication, directly or indirectly, with each other, forexample, via one or more buses 1345. The communications module 1335 maybe configured to communicate bi-directionally via one or more wired orwireless links 1340.

The design environment 1305 includes VRDN system model(s) 1350, whichmay include functional characteristics of a VRDN designed according toVRDN parameters 1365. VRDN parameters 1365 may include a set ofparameters for each VRDN system model 1350, which may include number ofstorage nodes N, type of storage node (which may be different fordifferent storage nodes), message retrieval reliability M_(rr) for eachstorage node, total storage L, message redundancy coding scheme, and/ormessage redundancy policy u(x).

Message delivery processor 1320 may calculate indirect link metrics 1360for one or more VRDN system model(s) 1350. For example, message deliveryprocessor 1320 may determine the probability of message availabilityP_(I) for one or more of the VRDN system model(s) 1350 based on VRDNparameters 1365 for the VRDN system model(s) 1350 and a message PDF 1370as described above with reference to block 1225 of FIG. 12.

VRDN state space processor 1380 may determine if the probability ofmessage availability P_(I) for one or more of the VRDN system model(s)1350 satisfies the condition P_(I)≥R₂/R₀ for indirect link metrics 1360(e.g., target values for R₂ and R₀). VRDN state space processor 1380 mayuse various techniques to modify the VRDN parameters 1365 for the VRDNsystem model(s) 1350 to traverse the state space of the system such asgradient ascent, monte carlo, simulating annealing, and the like. TheVRDN state space processor 1380 may iteratively modify the VRDNparameters 1365 for the VRDN system model(s) 1350 and the messagedelivery processor 1320 may calculate indirect link metrics 1360 for theupdated VRDN system model(s) 1350. The VRDN state space processor 1380may determine that one or more sets of VRDN parameters 1365 satisfy thecondition P_(I)≥R₂/R₀ for indirect link metrics 1360, and may furtherselect system components for a VRDN 130 by applying one or moreadditional metrics (e.g., a cost metric, a size metric, a weight metric,etc.).

The memory 1315 may include random access memory (RAM) and read onlymemory (ROM). The memory 1315 may store computer-readable,computer-executable software/firmware code 1325 including instructionsthat are configured to, when executed, cause the VRDN state spaceprocessor 1380 and message delivery processor 1320 to perform variousfunctions described herein (e.g., traverse the state space of thesystem, calculate indirect link metrics 1360 for the VRDN systemmodel(s) 1350, etc.). Alternatively, the software/firmware code 1325 maynot be directly executable by the performance metrics calculationprocessor 1320 but be configured to cause a computer (e.g., whencompiled and executed) to perform functions described herein. Theperformance metrics calculation processor 1320 may include anintelligent hardware device, e.g., a central processing unit (CPU), amicrocontroller, an ASIC, etc. may include RAM and ROM.

It should be noted that the methods, systems and devices discussed aboveare intended merely to be examples. It must be stressed that variousembodiments may omit, substitute, or add various procedures orcomponents as appropriate. For instance, it should be appreciated that,in alternative embodiments, the methods may be performed in an orderdifferent from that described, and that various steps may be added,omitted or combined. Also, features described with respect to certainembodiments may be combined in various other embodiments. Differentaspects and elements of the embodiments may be combined in a similarmanner. Also, it should be emphasized that technology evolves and, thus,many of the elements are exemplary in nature and should not beinterpreted to limit the scope of embodiments of the principlesdescribed herein.

Specific details are given in the description to provide a thoroughunderstanding of the embodiments. However, it will be understood by oneof ordinary skill in the art that the embodiments may be practicedwithout these specific details. For example, well-known circuits,processes, algorithms, structures, and techniques have been shownwithout unnecessary detail in order to avoid obscuring the embodiments.

Also, it is noted that the embodiments may be described as a processwhich is depicted as a flow diagram or block diagram. Although each maydescribe the operations as a sequential process, many of the operationscan be performed in parallel or concurrently. In addition, the order ofthe operations may be rearranged. A process may have additional stepsnot included in the figure. Processors may perform the necessary tasks.Features implementing functions may also be physically located atvarious positions, including being distributed such that portions offunctions are implemented at different physical locations.

Furthermore, embodiments may be implemented by hardware, software,firmware, middleware, microcode, hardware description languages, orcombinations thereof. When implemented in software, firmware, middlewareor microcode, the program code or code segments to perform the necessarytasks may be stored in a computer-readable medium such as a storagemedium. A computer-readable medium may include, for example, RAM, ROM,EEPROM, flash memory, CD-ROM or other optical disk storage, magneticdisk storage or other magnetic storage devices, or any other medium thatcan be used to carry or store desired program code means in the form ofinstructions or data structures and that can be accessed by ageneral-purpose or special-purpose computer, or a general-purpose orspecial-purpose processor.

As used herein, including in the claims, the term “and/or,” when used ina list of two or more items, means that any one of the listed items canbe employed by itself, or any combination of two or more of the listeditems can be employed. For example, if a composition is described ascontaining components A, B, and/or C, the composition can contain Aalone; B alone; C alone; A and B in combination; A and C in combination;B and C in combination; or A, B, and C in combination. Also, as usedherein, including in the claims, “or” as used in a list of items (forexample, a list of items prefaced by a phrase such as “at least one of”or “one or more of”) indicates a disjunctive list such that, forexample, a list of “at least one of A, B, or C” means A or B or C or ABor AC or BC or ABC (i.e., A and B and C).

Having described several embodiments, it will be recognized by those ofskill in the art that various modifications, alternative constructions,and equivalents may be used without departing from the spirit of theprinciples described herein. For example, the above elements may merelybe a component of a larger system, wherein other rules may takeprecedence over or otherwise modify the application of the principlesdescribed herein. Also, a number of steps may be undertaken before,during, or after the above elements are considered. Accordingly, theabove description should not be taken as limiting the scope of theinvention.

What is claimed is:
 1. A communication system comprising: a networkgateway device on a mobile platform coupled with a plurality of usercommunication devices on the mobile platform via respective localcommunication links; a ground station coupled with a network, thenetwork comprising at least one source node for a message library; adirect communication link coupling the ground station to the networkgateway device, the direct communication link to deliver messages of themessage library to the network gateway device from the ground station inresponse to requests by the plurality of user communication devices; anda variable redundancy delivery network on the mobile platform andcoupled with the network gateway device, the variable redundancydelivery network comprising one or more intermediate storage nodesstoring the messages with variable redundancy for delivery to theplurality of user communication devices in response to subsequent onesof the requests for the messages based on a non-uniform probabilitydensity of the requests for the messages, wherein at least one parameterof the variable redundancy delivery network is selected based at leastin part on a desired information rate to be provided by the variableredundancy delivery network, and wherein the non-uniform probabilitydensity of the messages is determined based on a number of the requestsfor the messages in a rolling time period.
 2. The communication systemof claim 1, wherein the variable redundancy for the storing of themessages comprises a storage policy for increasing redundancy based on anumber of times the messages have been delivered to the plurality ofuser communication devices.
 3. The communication system of claim 2,wherein the storage policy is determined based at least in part on astorage size of the one or more intermediate storage nodes or a numberof the one or more intermediate storage nodes.
 4. The communicationsystem of claim 2, wherein the storage policy is determined based atleast in part on a message retrieval reliability associated with thestored messages.
 5. The communication system of claim 2, wherein thestorage policy is determined based on an optimization process applied toa function of a probability of message availability.
 6. Thecommunication system of claim 2, wherein the storage policy is adaptedbased at least in part on an identified failure of a storage node of thevariable redundancy delivery network.
 7. The communication system ofclaim 2, wherein the storage policy is adapted based at least in part onan identified change of the non-uniform probability density of themessages.
 8. The communication system of claim 2, wherein the storagepolicy comprises message replication, parity coding, Reed-Solomoncoding, or a combination thereof.
 9. The communication system of claim1, wherein the one or more intermediate storage nodes of the variableredundancy delivery network are configured in a non-redundant disk arrayconfiguration.
 10. The communication system of claim 1, wherein thedirect communication link comprises a satellite communication linkbetween the ground station and the network gateway device.
 11. A methodfor capacity enhancement of a communications system, the methodcomprising: coupling a network gateway device on a mobile platform witha plurality of user communication devices on the mobile platform viarespective local communication links; coupling the network gatewaydevice with a ground station via a direct communication link, the groundstation coupled with a network, the network comprising at least onesource node for a message library; coupling the network gateway devicewith a variable redundancy delivery network on the mobile platform, thevariable redundancy delivery network comprising one or more intermediatestorage nodes, wherein at least one parameter of the variable redundancydelivery network is selected based at least in part on a desiredinformation rate to be provided by the variable redundancy deliverynetwork; delivering messages of the message library to the networkgateway device from the ground station in response to requests by theplurality of user communication devices; determining a non-uniformprobability density of the messages based on a number of the requestsfor the messages in a rolling time period; storing the messages fordelivery from the variable redundancy delivery network to the pluralityof user communication devices with variable redundancy based on thenon-uniform probability density of the requests for the messages; anddelivering the messages to the plurality of user communication devicesfrom the variable redundancy delivery network in response to subsequentones of the requests for the messages.
 12. The method of claim 11,wherein the variable redundancy for the storing of the messagescomprises a storage policy for increasing redundancy based on a numberof times the messages have been delivered to the plurality of usercommunication devices.
 13. The method of claim 12, wherein the storagepolicy is determined based at least in part on a storage size of the oneor more intermediate storage nodes or a number of the one or moreintermediate storage nodes.
 14. The method of claim 12, wherein thestorage policy is determined based at least in part on a messageretrieval reliability associated with the stored messages.
 15. Themethod of claim 12, wherein the storage policy is determined based on anoptimization process applied to a function of a probability of messageavailability.
 16. The method of claim 12, further comprising:identifying a failure of a storage node of the variable redundancydelivery network; and adapting the storage policy based at least in parton the identified failure of the storage node.
 17. The method of claim12, further comprising: identifying a change in the non-uniformprobability density of the messages; and adapting the storage policybased at least in part on the identified change in the non-uniformprobability density of the messages.
 18. The method of claim 12, whereinthe storage policy comprises message replication, parity coding,Reed-Solomon coding, or a combination thereof.
 19. The method of claim11, wherein the one or more intermediate storage nodes of the variableredundancy delivery network are configured in a non-redundant disk arrayconfiguration.
 20. The method of claim 11, wherein the directcommunication link comprises a satellite communication link between theground station and the network gateway device.
 21. A non-transitorycomputer readable medium storing code for capacity enhancement of acommunications system comprising a network gateway device on a mobileplatform coupled with a ground station via a direct communication linkand a variable redundancy delivery network on the mobile platform, thevariable redundancy delivery network comprising one or more intermediatestorage nodes, wherein at least one parameter of the variable redundancydelivery network is selected based at least in part on a desiredinformation rate to be provided by the variable redundancy deliverynetwork, the ground station coupled with a network that comprises atleast one source node for a message library, the code comprisinginstructions executable by a processor for: coupling the network gatewaydevice with a plurality of user communication devices on the mobileplatform via respective local communication links; delivering messagesof the message library to the network gateway device from the groundstation in response to requests by the plurality of user communicationdevices; determining a non-uniform probability density of the messagesbased on a number of the requests for the messages in a rolling timeperiod; storing the messages for delivery from the variable redundancydelivery network to the plurality of user communication devices withvariable redundancy based on the non-uniform probability density of therequests for the messages; and delivering the messages to the pluralityof user communication devices from the variable redundancy deliverynetwork in response to subsequent ones of the requests for the messages.